MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

In India the number of two-wheelers is greater than the cardinal number of parking spots available, hence people tend to park their vehicles at undesignated spots and open spaces which increases the risk of damage to the vehicle. To prevail over this situation, we contemplated, designed, and came up with a solution. Park Shield predominantly aims towards providing an all-inclusive system for two-wheeler vehicles that notifies the attempts of theft and live location tracking for your vehicle with absolute authentication of the users. The uniqueness of the system is that it can be controlled using an android application with authorized users registered on the database. In case the vehicle is hoisted or hauled, the live location update with an alert notification will be sent to the owner's cellular device via the application. © 2022 IEEE.

World University root node

School of Electronics & Communication Engineering

Engineering and Technology

2022 6th International Conference on Computing, Communication, Control and Automation, ICCUBEA 2022

Park-Shield: Two-Wheeler Anti-Theft System

&nbsp;Machine learning, a fragment of AI, is popularizing in every industrial domain and making a promising place for itself. It is flourishing for all the companies that are implementing ML. It very well possesses the ability to change the future of industries by offering better ways of working, instead of the existing traditional methods. The real estate sector has witnessed a quite similar situation in terms of the effect it has had on the sales of the real estate properties. ML has made business quite easy by predicting the sales prices of real estate properties on the basis of previous purchases and customer buying patterns. This project is about forecasting the house property prices in Bangalore city. It is accomplished by studying the various features of a particular house that fits appropriately into customer’s requirements, followed by deploying the linear regression ML model on the dataset. The study has shown that a linear regression model is a competent ML algorithm which is simple and at the same time gives accurate results. This project enlightens the fact that ML is a very good alternative for streamlining the business engagement in the real estate sector.

PENSEE

Real estate price prediction using Machine learning

Resting-state fMRI (rsfMRI) was firstly characterized by Biswal et al [1] in the year 1995 and since then it is used for studying patients with various neurosurgical, neurologic, and other brain-related disorders. Various statistical methods are used to analyze the resting-state functional magnetic resonance imaging connectivity. This paper attempts to explore more on the learning of resting-state functional magnetic resonance imaging connectivity. This study will help to understand the usage of rsfMRI to evaluate functional connectivity in the human brain and its usage for surgical decision-making for drug-resistant epilepsy. This paper explains the significance of such connectivity analysis, the methods available for it, and the shortcomings associated with the data.

School of Computer Engineering & Technology

2021 2nd International Conference for Emerging Technology, INCET 2021

Resting-State Functional Connectivity Analysis for diagnosis of Epilepsy patients

There is increase in the number of automobiles ,hence the air pollution is also increasing. It is very important to resolve theproblem of air pollution resulting from automobile exhaust gases.In this paper a system is proposed which uses Radio frequencyidentification (RFID) technology as a low-cost and mature wireless communication method to collect and transmit emission information ofvehicles and Internet of Things (IoT) concept is used. .Hence with the help of notification via the SMS the owner will be notified and furthermeasures will be taken.By applying the system, it is possible to smoothly realize a green traffic network.As the usage of vehicles is increasing drastically, the hazards due to vehicles is also increased. The main cause for accidents is high speed,drunk and drive, diverting minds, over stress and sometimes due to electronic gadgets. This paper also deals with accident detection systemthat occurs due to carelessness of the person who is driving the vehicle.This introduces accident alerting system which alerts the person whois driving the vehicle. If the person is not in a position to control the vehicle then the accident might occur. Once the accident occurs, thissystem will send information and location to the person’s emergency contact number.

IJCRT

Detection of Vehicle Emission and accident using IOT

International Journal of Scientific Research and Engineering Trends

INTELLIGENT TRAFFIC MONITORING SYSTEM USING IOT

Wireless automation in electricity and billing is the new innovation in terms of technology. Retrieving the data of units consumedby the consumers is not efficient. The current process of electricity billing is susceptible to errors. It is time and resource and laborconsuming as well. The problem of the billing system becomes crucial when consumers try to tamper the meter, thereby pay less amountthan what actually should be paid. In our proposed system, already installed energy meters at our houses are not replaced, but an additionalsmall circuit design along with IoT on the already installed meters can change the existing meters into smart meters. Smart Electricity meterusing Internet of Things (IoT) system present an efficient and cost-effective way to transfer the information of energy consumed to theconsumer wirelessly and automatically without any human intervention, as well as it provides facilities to detect the illegal usage of theelectricity. Aim of this project is to calculate the electricity consumption, formulate the bill automatically without any labor and transfer itusing IoT. Bill amount is SMSed through IoT platform to the consumer at the start of every month with the help of RTC. Also, this studyaims to detect and control the energy theft. A passive infrared (IR) sensor is engaged with the system to detect when any illegal alterationhappens in the metering system. In such case, the system itself will notify it to the server, as well as it has the facility to disconnect and reconnectthe electricity supply automatically using a Solid-State Relay, also the power supply can be disconnected and reconnected remotelyin case of pending bills.

IOT based smart energy meter

IJERT

AUTOMATED WATER POTABILITY MONITORING SYSTEM

International Journal of Engineering Research \& Technology (IJERT)

Customization of Arm Processor in Mixed Signal FPGA

Maintaining Social Distancing among people is very crucial at present when the whole world is facing the COVID-19 pandemic and yet there is no effective cure or antidotes available. In this pandemic situation, we need a robust solution to flatten the curve of COVID-19 so that people do not get sick, so our economy and supply chain stays running, and people's risk can be minimized. Some techniques are available to maintain social distancing, but most are based on visual recognition, which is not effectively applicable everywhere comparatively expensive. To overcome this issue and make it more reactive and smoother, an android application has been invented for the Social Distancing Alert System (SDAS). Our network is based on the concept of Bluetooth Low Energy (BLE) detection technology, which receives Transmission Power (TsPower) and Signal Strength Indicator (SSI) on user handsets for the assessment of real-time social distancing status and to alert them. It informs through popup at real-time to the users, warnings on the screen of the handsets and by vibration and notification sound when another app user gets closer to a range of 2 meters with four levels of granularity.&nbsp;